OLMo-1B's results seem very bad on olmo-eval

[Ivan-Zhou]

❓ The question

This is a cross-post from allenai/OLMo-Eval#31 for visibility.

I ran olmo_eval with allenai/OLMo-1B on the paloma dataset and I noticed two issues:

1. The evaluation metric seems worse than I anticipated, especially the ppl_token which seems too high. I wonder if that's an averaged or summed measurement. I add a screenshot below and you can see my full results in this google sheet.

2. This may be related to 1. I noticed when it inialized allenai/OLMo-1B, there's a warning that some many of the weights (if not all) are not initialized correctly. From the log below, it seems to be trying to initialize with the class OlmoForCausalLM.

Some weights of OlmoForCausalLM were not initialized from the model checkpoint at allenai/OLMo-1B and are newly initialized: ['lm_head.weight', 'model.embed_tokens.weight', 'model.layers.0.mlp.down_proj.weight', 'model.layers.0.mlp.gate_proj.weight', 'model.layers.0.mlp.up_proj.weight', 'model.layers.0.self_attn.k_proj.weight', 'model.layers.0.self_attn.o_proj.weight', 'model.layers.0.self_attn.q_proj.weight', 'model.layers.0.self_attn.v_proj.weight', 'model.layers.1.mlp.down_proj.weight', 'model.layers.1.mlp.gate_proj.weight', 'model.layers.1.mlp.up_proj.weight', 'model.layers.1.self_attn.k_proj.weight', 'model.layers.1.self_attn.o_proj.weight', 'model.layers.1.self_attn.q_proj.weight', 'model.layers.1.self_attn.v_proj.weight', 'model.layers.10.mlp.down_proj.weight', 'model.layers.10.mlp.gate_proj.weight', 'model.layers.10.mlp.up_proj.weight', 'model.layers.10.self_attn.k_proj.weight', 'model.layers.10.self_attn.o_proj.weight', 'model.layers.10.self_attn.q_proj.weight', 'model.layers.10.self_attn.v_proj.weight', 'model.layers.11.mlp.down_proj.weight', 'model.layers.11.mlp.gate_proj.weight', 'model.layers.11.mlp.up_proj.weight', 'model.layers.11.self_attn.k_proj.weight', 'model.layers.11.self_attn.o_proj.weight', 'model.layers.11.self_attn.q_proj.weight', 'model.layers.11.self_attn.v_proj.weight', 'model.layers.12.mlp.down_proj.weight', 'model.layers.12.mlp.gate_proj.weight', 'model.layers.12.mlp.up_proj.weight', 'model.layers.12.self_attn.k_proj.weight', 'model.layers.12.self_attn.o_proj.weight', 'model.layers.12.self_attn.q_proj.weight', 'model.layers.12.self_attn.v_proj.weight', 'model.layers.13.mlp.down_proj.weight', 'model.layers.13.mlp.gate_proj.weight', 'model.layers.13.mlp.up_proj.weight', 'model.layers.13.self_attn.k_proj.weight', 'model.layers.13.self_attn.o_proj.weight', 'model.layers.13.self_attn.q_proj.weight', 'model.layers.13.self_attn.v_proj.weight', 'model.layers.14.mlp.down_proj.weight', 'model.layers.14.mlp.gate_proj.weight', 'model.layers.14.mlp.up_proj.weight', 'model.layers.14.self_attn.k_proj.weight', 'model.layers.14.self_attn.o_proj.weight', 'model.layers.14.self_attn.q_proj.weight', 'model.layers.14.self_attn.v_proj.weight', 'model.layers.15.mlp.down_proj.weight', 'model.layers.15.mlp.gate_proj.weight', 'model.layers.15.mlp.up_proj.weight', 'model.layers.15.self_attn.k_proj.weight', 'model.layers.15.self_attn.o_proj.weight', 'model.layers.15.self_attn.q_proj.weight', 'model.layers.15.self_attn.v_proj.weight', 'model.layers.16.mlp.down_proj.weight', 'model.layers.16.mlp.gate_proj.weight', 'model.layers.16.mlp.up_proj.weight', 'model.layers.16.self_attn.k_proj.weight', 'model.layers.16.self_attn.o_proj.weight', 'model.layers.16.self_attn.q_proj.weight', 'model.layers.16.self_attn.v_proj.weight', 'model.layers.17.mlp.down_proj.weight', 'model.layers.17.mlp.gate_proj.weight', 'model.layers.17.mlp.up_proj.weight', 'model.layers.17.self_attn.k_proj.weight', 'model.layers.17.self_attn.o_proj.weight', 'model.layers.17.self_attn.q_proj.weight', 'model.layers.17.self_attn.v_proj.weight', 'model.layers.18.mlp.down_proj.weight', 'model.layers.18.mlp.gate_proj.weight', 'model.layers.18.mlp.up_proj.weight', 'model.layers.18.self_attn.k_proj.weight', 'model.layers.18.self_attn.o_proj.weight', 'model.layers.18.self_attn.q_proj.weight', 'model.layers.18.self_attn.v_proj.weight', 'model.layers.19.mlp.down_proj.weight', 'model.layers.19.mlp.gate_proj.weight', 'model.layers.19.mlp.up_proj.weight', 'model.layers.19.self_attn.k_proj.weight', 'model.layers.19.self_attn.o_proj.weight', 'model.layers.19.self_attn.q_proj.weight', 'model.layers.19.self_attn.v_proj.weight', 'model.layers.2.mlp.down_proj.weight', 'model.layers.2.mlp.gate_proj.weight', 'model.layers.2.mlp.up_proj.weight', 'model.layers.2.self_attn.k_proj.weight', 'model.layers.2.self_attn.o_proj.weight', 'model.layers.2.self_attn.q_proj.weight', 'model.layers.2.self_attn.v_proj.weight', 'model.layers.20.mlp.down_proj.weight', 'model.layers.20.mlp.gate_proj.weight', 'model.layers.20.mlp.up_proj.weight', 'model.layers.20.self_attn.k_proj.weight', 'model.layers.20.self_attn.o_proj.weight', 'model.layers.20.self_attn.q_proj.weight', 'model.layers.20.self_attn.v_proj.weight', 'model.layers.21.mlp.down_proj.weight', 'model.layers.21.mlp.gate_proj.weight', 'model.layers.21.mlp.up_proj.weight', 'model.layers.21.self_attn.k_proj.weight', 'model.layers.21.self_attn.o_proj.weight', 'model.layers.21.self_attn.q_proj.weight', 'model.layers.21.self_attn.v_proj.weight', 'model.layers.22.mlp.down_proj.weight', 'model.layers.22.mlp.gate_proj.weight', 'model.layers.22.mlp.up_proj.weight', 'model.layers.22.self_attn.k_proj.weight', 'model.layers.22.self_attn.o_proj.weight', 'model.layers.22.self_attn.q_proj.weight', 'model.layers.22.self_attn.v_proj.weight', 'model.layers.23.mlp.down_proj.weight', 'model.layers.23.mlp.gate_proj.weight', 'model.layers.23.mlp.up_proj.weight', 'model.layers.23.self_attn.k_proj.weight', 'model.layers.23.self_attn.o_proj.weight', 'model.layers.23.self_attn.q_proj.weight', 'model.layers.23.self_attn.v_proj.weight', 'model.layers.24.mlp.down_proj.weight', 'model.layers.24.mlp.gate_proj.weight', 'model.layers.24.mlp.up_proj.weight', 'model.layers.24.self_attn.k_proj.weight', 'model.layers.24.self_attn.o_proj.weight', 'model.layers.24.self_attn.q_proj.weight', 'model.layers.24.self_attn.v_proj.weight', 'model.layers.25.mlp.down_proj.weight', 'model.layers.25.mlp.gate_proj.weight', 'model.layers.25.mlp.up_proj.weight', 'model.layers.25.self_attn.k_proj.weight', 'model.layers.25.self_attn.o_proj.weight', 'model.layers.25.self_attn.q_proj.weight', 'model.layers.25.self_attn.v_proj.weight', 'model.layers.26.mlp.down_proj.weight', 'model.layers.26.mlp.gate_proj.weight', 'model.layers.26.mlp.up_proj.weight', 'model.layers.26.self_attn.k_proj.weight', 'model.layers.26.self_attn.o_proj.weight', 'model.layers.26.self_attn.q_proj.weight', 'model.layers.26.self_attn.v_proj.weight', 'model.layers.27.mlp.down_proj.weight', 'model.layers.27.mlp.gate_proj.weight', 'model.layers.27.mlp.up_proj.weight', 'model.layers.27.self_attn.k_proj.weight', 'model.layers.27.self_attn.o_proj.weight', 'model.layers.27.self_attn.q_proj.weight', 'model.layers.27.self_attn.v_proj.weight', 'model.layers.28.mlp.down_proj.weight', 'model.layers.28.mlp.gate_proj.weight', 'model.layers.28.mlp.up_proj.weight', 'model.layers.28.self_attn.k_proj.weight', 'model.layers.28.self_attn.o_proj.weight', 'model.layers.28.self_attn.q_proj.weight', 'model.layers.28.self_attn.v_proj.weight', 'model.layers.29.mlp.down_proj.weight', 'model.layers.29.mlp.gate_proj.weight', 'model.layers.29.mlp.up_proj.weight', 'model.layers.29.self_attn.k_proj.weight', 'model.layers.29.self_attn.o_proj.weight', 'model.layers.29.self_attn.q_proj.weight', 'model.layers.29.self_attn.v_proj.weight', 'model.layers.3.mlp.down_proj.weight', 'model.layers.3.mlp.gate_proj.weight', 'model.layers.3.mlp.up_proj.weight', 'model.layers.3.self_attn.k_proj.weight', 'model.layers.3.self_attn.o_proj.weight', 'model.layers.3.self_attn.q_proj.weight', 'model.layers.3.self_attn.v_proj.weight', 'model.layers.30.mlp.down_proj.weight', 'model.layers.30.mlp.gate_proj.weight', 'model.layers.30.mlp.up_proj.weight', 'model.layers.30.self_attn.k_proj.weight', 'model.layers.30.self_attn.o_proj.weight', 'model.layers.30.self_attn.q_proj.weight', 'model.layers.30.self_attn.v_proj.weight', 'model.layers.31.mlp.down_proj.weight', 'model.layers.31.mlp.gate_proj.weight', 'model.layers.31.mlp.up_proj.weight', 'model.layers.31.self_attn.k_proj.weight', 'model.layers.31.self_attn.o_proj.weight', 'model.layers.31.self_attn.q_proj.weight', 'model.layers.31.self_attn.v_proj.weight', 'model.layers.4.mlp.down_proj.weight', 'model.layers.4.mlp.gate_proj.weight', 'model.layers.4.mlp.up_proj.weight', 'model.layers.4.self_attn.k_proj.weight', 'model.layers.4.self_attn.o_proj.weight', 'model.layers.4.self_attn.q_proj.weight', 'model.layers.4.self_attn.v_proj.weight', 'model.layers.5.mlp.down_proj.weight', 'model.layers.5.mlp.gate_proj.weight', 'model.layers.5.mlp.up_proj.weight', 'model.layers.5.self_attn.k_proj.weight', 'model.layers.5.self_attn.o_proj.weight', 'model.layers.5.self_at
tn.q_proj.weight', 'model.layers.5.self_attn.v_proj.weight', 'model.layers.6.mlp.down_proj.weight', 'model.layers.6.mlp.gate_proj.weight', 'model.layers.6.mlp.up_proj.weight', 'model.layers.6.self_attn.k_proj.weight', 'model.layers.6.self_attn.o_proj.weight', 'model.layers.6.self_attn.q_proj.weight', 'model.layers.6.self_attn.v_proj.weight', 'model.layers.7.mlp.down_proj.weight', 'model.layers.7.mlp.gate_proj.weight', 'model.layers.7.mlp.up_proj.weight', 'model.layers.7.self_attn.k_proj.weight', 'model.layers.7.self_attn.o_proj.weight', 'model.layers.7.self_attn.q_proj.weight', 'model.layers.7.self_attn.v_proj.weight', 'model.layers.8.mlp.down_proj.weight', 'model.layers.8.mlp.gate_proj.weight', 'model.layers.8.mlp.up_proj.weight', 'model.layers.8.self_attn.k_proj.weight', 'model.layers.8.self_attn.o_proj.weight', 'model.layers.8.self_attn.q_proj.weight', 'model.layers.8.self_attn.v_proj.weight', 'model.layers.9.mlp.down_proj.weight', 'model.layers.9.mlp.gate_proj.weight', 'model.layers.9.mlp.up_proj.weight', 'model.layers.9.self_attn.k_proj.weight', 'model.layers.9.self_attn.o_proj.weight', 'model.layers.9.self_attn.q_proj.weight', 'model.layers.9.self_attn.v_proj.weight']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.

The configuration and environment I use to reproduce this results can be found in the issue allenai/OLMo-Eval#31